Basim Azam
Postdoctoral Research Fellow @ The University of Melbourne
School of Computing and Information Sciences (CIS)
The University of Melbourne, Melbourne, Australia
basim.azam@unimelb.edu.au
Biography
Basim Azam has worked as Graduate Research Assistant in Artificial Intelligence and Computer Vision (iVision) Lab and completed his Master of Science degree at Electrical Engineering department, Institute of Space Technology, Islamabad. He received his Bachelor of Science degree in Electrical Engineering from COMSATS University Islamabad in 2017. His research interests include artificial intelligence, computer vision, object detection, image segmentation, image generation, machine learning and specifically neural networks.
Experience
Postdoctoral Research Fellow [Jan 2024 - Present]
School of Computing and Information Sciences (CIS)
Faculty of Engineering & Information Technology (FEIT)
The University of Melbourne, Melbourne, Australia
Postdoctoral Research Fellow [Mar 2023 - Jan 2024]
Institute for Integrated and Intelligent Systems
School of Information and Communication Technology
Griffith University, Brisbane, Australia
Graduate Research Assistant [Nov 2018 - Nov 2019]
iVision - Artificial Intelligence & Computer Vision Lab
Electrical Engineering Department
Institute of Space Technology Islamabad, Pakistan
Lab Engineer [Jan 2019 - June 2019]
Electrical & Computer Engineering Department
Air University – Islamabad
Courses taught: Computer Programming, Electric Circuit Analysis.
Education
Ph.D. - Doctor of Philosophy (Artificial Intelligence - Computer Vision) [Apr 2020 - Apr 2023]
Intsitute of Integrated and Intelligent Systems, Griffith University, Brisbane, Australia
ARC Discovery Project Living Stipend Scholarship Award and International Excellence Award.
(Image Parsing, Pixel-wise Segmentation, Semantic Segmentation, Deep Learning)
MS Electrical Engineering (Signal & Image Processing) [Aug 2017- Oct 2019]
Institute of Space Technology, Islamabad, Pakistan
PEEF Merit Scholarship - Tuition Fee Wavier and Stipend Scholarship
(Object Detection, Machine Learning, Deep Learning, Neural Networks )
BS Electrical Engineering [Jun 2013- Jun 2017]
COMSATS University Islambad, Wah Campus, Wah Cantt. Pakistan
(Digital Image Processing, Artificial Neural Networks)
Publications
Journal
B. Azam, R. Mandal and B. Verma, “Relationship Aware Contextual Adaptive and Decisive Feature Ranking Network for Image Parsing” in Information Sciences, vol 607, pp. 506-518, (2022) (IF:8.23)
S. Khan, B. Azam, W. Chen “Deep Collaborative Network with Alpha Matte for Precise Knee Tissue Segmentation from MRI” in Computer Methods and Programs in Biomedicine, (2022). (IF:7.03)
B. Azam, M.J. Khan, F.A. Bhatti, S.F. Hussain, A.J. Hashmi, K. Khurshid, “Aircraft Detection in Satellite Images with Deep Learning-based Object Detectors: A Comparative Study” in Microprocessor and Microsystems 2022. (IF:3.50)
B. Azam and B. Verma, “Automated Optimal Parameter Selection for Context Adaptive Deep Learning Framework for Image Parsing in Remote Sensing Imagery” in Expert System with Applications 2022 (Manuscript Under Review)
R. Mandal, B. Azam, B. Verma and M. Zhang “A Deep Learning Framework with GA-based Salient Visual Feature and Context Integration for Scene Parsing” in IEEE Transaction on Cybernetics, (2022) (Manuscript Under Review)
Conference
R. Mandal, B. Azam and B. Verma, “A Novel Optimized Context-Based Deep Architecture for Scene Parsing” in International Conference on Neural Information Processing (ICONIP), 2022. (Accepted)
R. Mandal, B. Azam and B. Verma, “Genetic Algorithms for Optimising Context-based Neural Networks for Image Segmentation” in International IEEE Symposium Series on Computational Intelligence (IEEE SSCI), 2022. (Accepted)
B. Azam, R. Mandal, and B. Verma, “Fully Convolutional Neural Network with Relation Aware Context Information for Image Parsing” in International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2021, Gold Coast, Australia.
B. Azam, R. Mandal, B. Verma “Relationship Aware Context Adaptive Feature Selection Framework for Image Parsing” International Joint Conference on Neural Network (IJCNN), 2021, Shenzhen, China.
R. Mandal, B. Azam, and B. Verma “Context-based Deep Learning Architecture with Optimal Integration Layer for Image Parsing”, in International Conference on Neural Information Processing (ICONIP), 2021. Bali, Indonesia.
R. Mandal, B. Azam, B. Verma and M. Zhang, “Deep Learning Model with GA-based Visual Feature Selection and Context Integration” in IEEE Congress on Evolutionary Computations (CEC), 2021, Kraków, Poland.
B. Azam, R. Mandal, L. Zhang, B. Verma “Class Probabilities Based Visual Features with Contextual Features for Image Parsing” 2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ), Wellington, New Zealand, 2020, pp. 1-6
W. Khan, B. Azam, N. Shahid, A. Khan, A. Shaheen “Formal Verification of Digital Circuits Using Simulator with Mathematical Foundation”. Applied Mechanics and Materials, Vol. 892, pp. 134-142, 2019
Technical Skills
Programming Languages
C++, Python, Verilog HDL, Veriformal, HTML, R, Latex
Software
MATLAB, Proteus, Packet Tracer, Model Sim, Arduino IDE, R Studio , Eclipse, Adobe Creative Suit, Microsoft Office
OS
Windows and Linux
Expertise
Research in Deep Learning based Object Detection.
Research in blurry and noisy Images to extract features.
Programming in C++, MATLAB, R and Python.
Experience of working and tutoring in Linux Environment.
Fluency in English (IELTS Overall band 7.5)
Scored 99 percentile in GAT Entrance Exam.